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Attila Biro

0000-0002-0430-9932

Innovation and Technology Leader | 2xPhD | Researcher (Engineering; Information and computing sciences; Health sciences)

Budapest

Dr. Biró is an accomplished and performance-driven professional with extensive experience in international business, software development, and scientific research in the IT and medical fields. He holds two PhDs: one in Informatics (from the UMFST G.E. Palade Târgu Mureș, Romania) and another in Health Sciences (from the University of Málaga, Spain). He is currently pursuing his third PhD degree in Applied Mathematics at Obuda University (Hungary). He earned his Master of Engineering (MEng) degree in Automatics and Industrial Informatics in 2001, followed by a second MEng degree in Advanced Automated Systems in 2002, with a specialization in Industrial and Energy Process Control. Since 2017, he has been deeply involved in the fields of sports science and medicine.

Currently, he acts as a research fellow at Óbuda University, a researcher at Malaga University (Clinimetria Group), and a lecturer at UMFST G.E. Palade Tg. Mures (Romania) and Sapientia Hungarian University of Transylvania [EMTE] (Romania). His primary research interests include sports medicine, rehabilitation, and AI-supported cybernetics. As CTO and CBDO (at ITware, Hungary), he is responsible for delivering secure, stable, effective, and innovative technology solutions as well as bringing creative problem-solving to B2B, R+D+I, and B2C projects by removing the complexity and identifying clear paths of implementation for efficient business operations.

Publications

  • Assessment of the Quality of Mobile Applications (Apps) for Management of Low Back Pain Using the Mobile App Rating Scale (MARS)
  • Evaluation of Android and Apple Store Depression Applications Based on Mobile Application Rating Scale
  • Tools for Evaluating the Content, Efficacy, and Usability of Mobile Health Apps According to the Consensus-Based Standards for the Selection of Health Measurement Instruments: Systematic Review (Preprint)
  • Tools for Evaluating the Content, Efficacy, and Usability of Mobile Health Apps According to the Consensus-Based Standards for the Selection of Health Measurement Instruments: Systematic Review
  • The Validity of the Energy Expenditure Criteria Based on Open Source Code through two Inertial Sensors
  • Reliability Study of Inertial Sensors LIS2DH12 Compared to ActiGraph GT9X: Based on Free Code
  • Visual Object Detection with DETR to Support Video-Diagnosis Using Conference Tools
  • Behavior Change Techniques and the Effects Associated With Digital Behavior Change Interventions in Sedentary Behavior in the Clinical Population: A Systematic Review
  • Tools for evaluating the content, efficacy, and usability of mobile health apps according to the consensus-based standards for the selection of health measurement instruments: systematic review
  • 広浦雅敏;” 異文化交流による M2M・IoT 製品 Kojimori の開発と市場開拓”
  • Evaluation of Android and Apple Store depression applications based on mobile application rating scale
  • Assessment of the quality of mobile applications (apps) for management of low back pain using the Mobile App Rating Scale (MARS)
  • Assessment of the quality of mobile applications (apps) for management of low back pain using the Mobile App Rating Scale (MARS) Int J Environ Res Public Health. 2020 Dec 09; 17 (24): 9209. doi: 10.3390/ijerph17249209
  • Development of Sake Brewing Entrepreneurs Support System in Fukushima
  • Machine Learning on Prediction of Relative Physical Activity Intensity Using Medical Radar Sensor and 3D Accelerometer
  • Synthetized Multilanguage OCR Using CRNN and SVTR Models for Realtime Collaborative Tools
  • Effectiveness of a gamified digital intervention based on lifestyle modification (iGAME) in secondary prevention: a protocol for a randomised controlled trial
  • Optimal Training Dataset Preparation for AI-Supported Multilanguage Real-Time OCRs Using Visual Methods
  • Precognition of mental health and neurogenerative disorders using AI-parsed text and sentiment analysis
  • AI-Assisted Fatigue and Stamina Control for Performance Sports on IMU-Generated Multivariate Times Series Datasets
  • Predictive Sports Strategy Approach Using YOLO and YOLO-NAS in Performance Sports
  • Applied AI for Real-Time Detection of Lesions and Tumors Following Severe Head Injuries
  • Gamification, GenAI and Reinforcement Learning as Motivational Assets in Performance Sports

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Co-workers & collaborators

  • László Szilágyi

  • Sándor Miklós Szilágyi

  • Jaime Martin Martin

  • Antonio Cuesta-Vargas

  • Antonio Ignacio Cuesta-Vargas

  • Laszlo Barna Iantovics

Attila Biro's public data